scholarly journals A sequence-based computational method for prediction of MoRFs

RSC Advances ◽  
2017 ◽  
Vol 7 (31) ◽  
pp. 18937-18945 ◽  
Author(s):  
Yu Wang ◽  
Yanzhi Guo ◽  
Xuemei Pu ◽  
Menglong Li

Molecular recognition features (MoRFs) are relatively short segments (10–70 residues) within intrinsically disordered regions (IDRs) that can undergo disorder-to-order transitions during binding to partner proteins.

Author(s):  
Jack Hanson ◽  
Thomas Litfin ◽  
Kuldip Paliwal ◽  
Yaoqi Zhou

Abstract Motivation Protein intrinsic disorder describes the tendency of sequence residues to not fold into a rigid three-dimensional shape by themselves. However, some of these disordered regions can transition from disorder to order when interacting with another molecule in segments known as molecular recognition features (MoRFs). Previous analysis has shown that these MoRF regions are indirectly encoded within the prediction of residue disorder as low-confidence predictions [i.e. in a semi-disordered state P(D)≈0.5]. Thus, what has been learned for disorder prediction may be transferable to MoRF prediction. Transferring the internal characterization of protein disorder for the prediction of MoRF residues would allow us to take advantage of the large training set available for disorder prediction, enabling the training of larger analytical models than is currently feasible on the small number of currently available annotated MoRF proteins. In this paper, we propose a new method for MoRF prediction by transfer learning from the SPOT-Disorder2 ensemble models built for disorder prediction. Results We confirm that directly training on the MoRF set with a randomly initialized model yields substantially poorer performance on independent test sets than by using the transfer-learning-based method SPOT-MoRF, for both deep and simple networks. Its comparison to current state-of-the-art techniques reveals its superior performance in identifying MoRF binding regions in proteins across two independent testing sets, including our new dataset of >800 protein chains. These test chains share <30% sequence similarity to all training and validation proteins used in SPOT-Disorder2 and SPOT-MoRF, and provide a much-needed large-scale update on the performance of current MoRF predictors. The method is expected to be useful in locating functional disordered regions in proteins. Availability and implementation SPOT-MoRF and its data are available as a web server and as a standalone program at: http://sparks-lab.org/jack/server/SPOT-MoRF/index.php. Contact [email protected] or [email protected] Supplementary information Supplementary data are available at Bioinformatics online.


Author(s):  
Zoya Shafat ◽  
Anwar Ahmed ◽  
Mohammad K. Parvez ◽  
Shama Parveen

Abstract Background Hepatitis E is a liver disease caused by the pathogen hepatitis E virus (HEV). The largest polyprotein open reading frame 1 (ORF1) contains a nonstructural Y-domain region (YDR) whose activity in HEV adaptation remains uncharted. The specific role of disordered regions in several nonstructural proteins has been demonstrated to participate in the multiplication and multiple regulatory functions of the viruses. Thus, intrinsic disorder of YDR including its structural and functional annotation was comprehensively studied by exploiting computational methodologies to delineate its role in viral adaptation. Results Based on our findings, it was evident that YDR contains significantly higher levels of ordered regions with less prevalence of disordered residues. Sequence-based analysis of YDR revealed it as a “dual personality” (DP) protein due to the presence of both structured and unstructured (intrinsically disordered) regions. The evolution of YDR was shaped by pressures that lead towards predominance of both disordered and regularly folded amino acids (Ala, Arg, Gly, Ile, Leu, Phe, Pro, Ser, Tyr, Val). Additionally, the predominance of characteristic DP residues (Thr, Arg, Gly, and Pro) further showed the order as well as disorder characteristic possessed by YDR. The intrinsic disorder propensity analysis of YDR revealed it as a moderately disordered protein. All the YDR sequences consisted of molecular recognition features (MoRFs), i.e., intrinsic disorder-based protein–protein interaction (PPI) sites, in addition to several nucleotide-binding sites. Thus, the presence of molecular recognition (PPI, RNA binding, and DNA binding) signifies the YDR’s interaction with specific partners, host membranes leading to further viral infection. The presence of various disordered-based phosphorylation sites further signifies the role of YDR in various biological processes. Furthermore, functional annotation of YDR revealed it as a multifunctional-associated protein, due to its susceptibility in binding to a wide range of ligands and involvement in various catalytic activities. Conclusions As DP are targets for regulation, thus, YDR contributes to cellular signaling processes through PPIs. As YDR is incompletely understood, therefore, our data on disorder-based function could help in better understanding its associated functions. Collectively, our novel data from this comprehensive investigation is the first attempt to delineate YDR role in the regulation and pathogenesis of HEV.


2013 ◽  
Vol 454 (3) ◽  
pp. 361-369 ◽  
Author(s):  
Alexander Cumberworth ◽  
Guillaume Lamour ◽  
M. Madan Babu ◽  
Jörg Gsponer

Because of their pervasiveness in eukaryotic genomes and their unique properties, understanding the role that ID (intrinsically disordered) regions in proteins play in the interactome is essential for gaining a better understanding of the network. Especially critical in determining this role is their ability to bind more than one partner using the same region. Studies have revealed that proteins containing ID regions tend to take a central role in protein interaction networks; specifically, they act as hubs, interacting with multiple different partners across time and space, allowing for the co-ordination of many cellular activities. There appear to be three different modules within ID regions responsible for their functionally promiscuous behaviour: MoRFs (molecular recognition features), SLiMs (small linear motifs) and LCRs (low complexity regions). These regions allow for functionality such as engaging in the formation of dynamic heteromeric structures which can serve to increase local activity of an enzyme or store a collection of functionally related molecules for later use. However, the use of promiscuity does not come without a cost: a number of diseases that have been associated with ID-containing proteins seem to be caused by undesirable interactions occurring upon altered expression of the ID-containing protein.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Vikas A. Tillu ◽  
James Rae ◽  
Ya Gao ◽  
Nicholas Ariotti ◽  
Matthias Floetenmeyer ◽  
...  

AbstractCaveolae are spherically shaped nanodomains of the plasma membrane, generated by cooperative assembly of caveolin and cavin proteins. Cavins are cytosolic peripheral membrane proteins with negatively charged intrinsically disordered regions that flank positively charged α-helical regions. Here, we show that the three disordered domains of Cavin1 are essential for caveola formation and dynamic trafficking of caveolae. Electrostatic interactions between disordered regions and α-helical regions promote liquid-liquid phase separation behaviour of Cavin1 in vitro, assembly of Cavin1 oligomers in solution, generation of membrane curvature, association with caveolin-1, and Cavin1 recruitment to caveolae in cells. Removal of the first disordered region causes irreversible gel formation in vitro and results in aberrant caveola trafficking through the endosomal system. We propose a model for caveola assembly whereby fuzzy electrostatic interactions between Cavin1 and caveolin-1 proteins, combined with membrane lipid interactions, are required to generate membrane curvature and a metastable caveola coat.


Sign in / Sign up

Export Citation Format

Share Document